output
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1542
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.2823 | 1.0 | 384 | 0.1897 |
| 0.2134 | 2.0 | 768 | 0.1762 |
| 0.1961 | 3.0 | 1152 | 0.1714 |
| 0.1855 | 4.0 | 1536 | 0.1693 |
| 0.1777 | 5.0 | 1920 | 0.1738 |
| 0.1713 | 6.0 | 2304 | 0.1674 |
| 0.1664 | 7.0 | 2688 | 0.1681 |
| 0.1613 | 8.0 | 3072 | 0.1733 |
| 0.1578 | 9.0 | 3456 | 0.1698 |
| 0.1542 | 10.0 | 3840 | 0.1622 |
| 0.1505 | 11.0 | 4224 | 0.1666 |
| 0.1475 | 12.0 | 4608 | 0.1655 |
| 0.1451 | 13.0 | 4992 | 0.1651 |
| 0.1426 | 14.0 | 5376 | 0.1646 |
| 0.1409 | 15.0 | 5760 | 0.1618 |
| 0.1385 | 16.0 | 6144 | 0.1617 |
| 0.1366 | 17.0 | 6528 | 0.1591 |
| 0.1347 | 18.0 | 6912 | 0.1628 |
| 0.1325 | 19.0 | 7296 | 0.1598 |
| 0.1313 | 20.0 | 7680 | 0.1606 |
| 0.1295 | 21.0 | 8064 | 0.1573 |
| 0.1285 | 22.0 | 8448 | 0.1587 |
| 0.1276 | 23.0 | 8832 | 0.1639 |
| 0.1258 | 24.0 | 9216 | 0.1608 |
| 0.1244 | 25.0 | 9600 | 0.1599 |
| 0.1234 | 26.0 | 9984 | 0.1584 |
| 0.1225 | 27.0 | 10368 | 0.1604 |
| 0.1214 | 28.0 | 10752 | 0.1570 |
| 0.1207 | 29.0 | 11136 | 0.1575 |
| 0.1195 | 30.0 | 11520 | 0.1563 |
| 0.1186 | 31.0 | 11904 | 0.1602 |
| 0.1177 | 32.0 | 12288 | 0.1595 |
| 0.1167 | 33.0 | 12672 | 0.1582 |
| 0.1159 | 34.0 | 13056 | 0.1556 |
| 0.1149 | 35.0 | 13440 | 0.1564 |
| 0.114 | 36.0 | 13824 | 0.1567 |
| 0.1132 | 37.0 | 14208 | 0.1551 |
| 0.1125 | 38.0 | 14592 | 0.1560 |
| 0.1113 | 39.0 | 14976 | 0.1537 |
| 0.1114 | 40.0 | 15360 | 0.1518 |
| 0.1103 | 41.0 | 15744 | 0.1585 |
| 0.1098 | 42.0 | 16128 | 0.1552 |
| 0.1094 | 43.0 | 16512 | 0.1533 |
| 0.1087 | 44.0 | 16896 | 0.1542 |
| 0.1081 | 45.0 | 17280 | 0.1505 |
| 0.1085 | 46.0 | 17664 | 0.1535 |
| 0.1075 | 47.0 | 18048 | 0.1526 |
| 0.1069 | 48.0 | 18432 | 0.1521 |
| 0.1067 | 49.0 | 18816 | 0.1532 |
| 0.1063 | 50.0 | 19200 | 0.1522 |
| 0.1056 | 51.0 | 19584 | 0.1522 |
| 0.1048 | 52.0 | 19968 | 0.1538 |
| 0.1048 | 53.0 | 20352 | 0.1534 |
| 0.1051 | 54.0 | 20736 | 0.1519 |
| 0.1045 | 55.0 | 21120 | 0.1542 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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